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← An AI loop can climb to a local maximum but then plateaus, and human intuition is needed to find the next hill.
17 connected korrents · 17 moments from 1 Oct 2023 to 21 Sept 2026.
Everything filed under LLMs
LLMs
Everything filed under robotics
robotics
Everything filed under reinforcement learning
reinforcement learning
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AI alignment
Everything filed under AI agents
AI agents
Everything filed under AI and human skill
AI and human skill
Everything filed under mathematics
mathematics
Everything filed under AGI
AGI Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Read this korrent: An AI loop can climb to a local maximum but then plateaus, and human intuition is needed to find the next hill. An AI loop can climb to a local maximum but then plateaus, and human intuition is needed to find the next hill. Last stated 4 weeks ago
6 Sept 2026
AA
Anish Acharya — holds since 2026-09-06 — tap for who they are
Same subject: A robot going down a wrong path is not producing training data; the efficient move is for a human to intervene and show the recovery. — tap to centre the map on it A robot going down a wrong path is not producing training data; the efficient move is for a human to intervene and show the recovery. Last stated 2 months ago
12 Aug 2026
CF
Chelsea Finn — holds since 2026-08-12 — tap for who they are
Same subject: You need to build early with AI to have any intuition for when the models become capable. — tap to centre the map on it You need to build early with AI to have any intuition for when the models become capable. Last stated 3 weeks ago
10 Sept 2026
MK
Mike Krieger — holds since 2026-09-10 — tap for who they are
Same subject: A swarm of agents with the right loop and the right metric can already out-produce a team of a hundred engineers. — tap to centre the map on it A swarm of agents with the right loop and the right metric can already out-produce a team of a hundred engineers. Last stated 2 months ago
29 Jul 2026
AW
Alexandr Wang — holds since 2026-07-29 — tap for who they are
Same subject: An iterative loop where society and AI evolve together offers the best chance of getting AI development right. — tap to centre the map on it An iterative loop where society and AI evolve together offers the best chance of getting AI development right. Last stated a month ago
1 Sept 2026
SA
Sam Altman — holds since 2026-09-01 — tap for who they are
Same subject: AI can supply the instruction and the feedback in a practice loop, but it cannot supply the middle step, which is doing the work. — tap to centre the map on it AI can supply the instruction and the feedback in a practice loop, but it cannot supply the middle step, which is doing the work. Last stated 2 months ago
22 Jul 2026
SY
Scott H. Young — holds since 2026-07-22 — tap for who they are
Same subject: AI helps exactly as far as the work is predictable and well documented, and stops helping on anything cutting edge. — tap to centre the map on it AI helps exactly as far as the work is predictable and well documented, and stops helping on anything cutting edge. Last stated 2 years ago
22 Mar 2025
TH
ThePrimeagen — holds since 2025-03-22 — tap for who they are
Same subject: What AI still cannot do in mathematics is build cumulatively on partial progress; it is trial, error and brute force rather than an idea improving through use. — tap to centre the map on it What AI still cannot do in mathematics is build cumulatively on partial progress; it is trial, error and brute force rather than an idea improving through use. Last stated 6 months ago
20 Mar 2026
TT
Terence Tao — holds since 2026-03-20 — tap for who they are
Same subject: An end-to-end self-improving AI is probably possible, but it is not even desirable, because it is a hard-takeoff scenario. — tap to centre the map on it An end-to-end self-improving AI is probably possible, but it is not even desirable, because it is a hard-takeoff scenario. Last stated a year ago
23 Jul 2025
DH
Demis Hassabis — holds since 2025-07-23 — tap for who they are
Same subject: A highly dynamic economy that cheaply mass-produces robots may increase rather than decrease the risk of Malthusian resource dilemmas. — tap to centre the map on it A highly dynamic economy that cheaply mass-produces robots may increase rather than decrease the risk of Malthusian resource dilemmas. Last stated 3 years ago
1 Oct 2023
TC
Tyler Cowen — holds since 2023-10-01 — tap for who they are
Same subject: A humanoid robot is the wrong tool on a factory floor, because a machine specialised in the task beats it. — tap to centre the map on it A humanoid robot is the wrong tool on a factory floor, because a machine specialised in the task beats it. Last stated a year ago
6 Apr 2025
MH
Molson Hart — holds since 2025-04-06 — tap for who they are
Same subject: A physical AI agent has to be safe on day one, because you cannot ship something merely good enough and let users find the edge cases. — tap to centre the map on it A physical AI agent has to be safe on day one, because you cannot ship something merely good enough and let users find the edge cases. Last stated 2 months ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — tap for who they are
Same subject: A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated. — tap to centre the map on it A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated. Last stated 4 months ago
4 Jun 2026
AI
Alex Imas — holds since 2026-06-04 — tap for who they are
Same subject: A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted. — tap to centre the map on it A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted. Last stated a year ago
7 Jun 2025
GM
Gary Marcus — holds since 2025-06-07 — tap for who they are
Same subject: A model that could learn effectively from raw bitstrings or bytestrings would be extremely powerful, able to learn from any data modality — tap to centre the map on it A model that could learn effectively from raw bitstrings or bytestrings would be extremely powerful, able to learn from any data modality Last stated 3 years ago
10 Oct 2023
CH
Chip Huyen — holds since 2023-10-10 — tap for who they are
Same subject: A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel. — tap to centre the map on it A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel. Last stated 2 months ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — tap for who they are
Same subject: A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well. — tap to centre the map on it A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well. Last stated 10 months ago
17 Nov 2025
AK
Andrej Karpathy — holds since 2025-11-17 — tap for who they are
Same subject: Better execution environments are needed for LLMs to properly utilize their ability to evolve systems. — tap to centre the map on it Better execution environments are needed for LLMs to properly utilize their ability to evolve systems. Last stated 2 weeks ago
21 Sept 2026
TL
Tobias Lütke — holds since 2026-09-21 — tap for who they are
At the centre
An AI loop can climb to a local maximum but then plateaus, and human intuition is needed to find the next hill.
Holds Read this korrent →
A robot going down a wrong path is not producing training data; the efficient move is for a human to intervene and show the recovery.
Holds
You need to build early with AI to have any intuition for when the models become capable.
Holds
A swarm of agents with the right loop and the right metric can already out-produce a team of a hundred engineers.
Holds
An iterative loop where society and AI evolve together offers the best chance of getting AI development right.
Holds
AI can supply the instruction and the feedback in a practice loop, but it cannot supply the middle step, which is doing the work.
Holds
AI helps exactly as far as the work is predictable and well documented, and stops helping on anything cutting edge.
Holds
What AI still cannot do in mathematics is build cumulatively on partial progress; it is trial, error and brute force rather than an idea improving through use.
Holds
An end-to-end self-improving AI is probably possible, but it is not even desirable, because it is a hard-takeoff scenario.
Holds
A highly dynamic economy that cheaply mass-produces robots may increase rather than decrease the risk of Malthusian resource dilemmas.
Holds
A humanoid robot is the wrong tool on a factory floor, because a machine specialised in the task beats it.
Holds
A physical AI agent has to be safe on day one, because you cannot ship something merely good enough and let users find the edge cases.
Holds
A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated.
Holds
A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted.
Holds
A model that could learn effectively from raw bitstrings or bytestrings would be extremely powerful, able to learn from any data modality
Holds
A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel.
Holds
A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well.
Holds
Better execution environments are needed for LLMs to properly utilize their ability to evolve systems.
Holds